Visual sentiment analysis on Twitter data streams

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2011
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Hao, Ming
Dayal, Umeshwar
Haug, Lars-Erik
Hsu, Mei-Chun
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2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2011, pp. 277-278. ISBN 978-1-4673-0015-5. Available under: doi: 10.1109/VAST.2011.6102472
Zusammenfassung

Twitter currently receives about 190 million tweets (small textbased Web posts) a day, in which people share their comments regarding a wide range of topics. A large number of tweets include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for evaluating customer sentiment. To explore high-volume twitter data, we introduce three novel timebased visual sentiment analysis techniques: (1) topic-based sentiment analysis that extracts, maps, and measures customer opinions; (2) stream analysis that identifies interesting tweets based on their density, negativity, and influence characteristics; and (3) pixel cell-based sentiment calendars and high density geo maps that visualize large volumes of data in a single view. We applied these techniques to a variety of twitter data, (e.g., movies, amusement parks, and hotels) to show their distribution and patterns, and to identify influential opinions.

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2011 IEEE Conference on Visual Analytics Science and Technology (VAST), 23. Okt. 2011 - 28. Okt. 2011, Providence, RI, USA
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ISO 690HAO, Ming, Christian ROHRDANTZ, Halldor JANETZKO, Umeshwar DAYAL, Daniel A. KEIM, Lars-Erik HAUG, Mei-Chun HSU, 2011. Visual sentiment analysis on Twitter data streams. 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). Providence, RI, USA, 23. Okt. 2011 - 28. Okt. 2011. In: 2011 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE, 2011, pp. 277-278. ISBN 978-1-4673-0015-5. Available under: doi: 10.1109/VAST.2011.6102472
BibTex
@inproceedings{Hao2011-10Visua-19048,
  year={2011},
  doi={10.1109/VAST.2011.6102472},
  title={Visual sentiment analysis on Twitter data streams},
  isbn={978-1-4673-0015-5},
  publisher={IEEE},
  booktitle={2011 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  pages={277--278},
  author={Hao, Ming and Rohrdantz, Christian and Janetzko, Halldor and Dayal, Umeshwar and Keim, Daniel A. and Haug, Lars-Erik and Hsu, Mei-Chun}
}
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